The adoption of online and virtual material in higher education continues to grow (National Center for Education Statistics, 2020), particularly in light of the shift to remote learning due to the COVID-19 pandemic. Although there are challenges, lecture-based materials lend themselves more naturally to being adapted for remote delivery of full courses, whereas laboratory-based courses lag behind. A general sentiment has persisted that computer-based labs cannot outright replace face-to-face (FTF) lab instruction (Bohr, 2014; Doiron, 2009). This wariness has similarly been reported in student groups (Dewhurst et al., 2000; Stuckey-Mickell & Stuckey-Danner, 2007).

Despite this initial wave of apprehension, more colleges and universities are beginning to adapt to fully or partially online physical science lab courses. This shift has been encouraged by recent reports that demonstrate equal or increased cognitive learning in virtual labs in biology (Reece & Butler, 2017), chemistry (Rowe et al., 2018), health sciences (Bloodgood, 2012), physics (Theyßen et al., 2016), and general science (Miller et al., 2018). These demonstrated successes—paired with the benefits of decreased costs, decreased physical waste, and increased accessibility (Wright, 2020)—make virtual science labs an increasingly enticing option.

Although there is a growing body of evidence for the potential of virtual physical science labs in knowledge acquisition, research explicitly focusing on student perceptions and affective learning is scarce. The importance of the affective domain in learning has long been understood (Lynch et al., 2009), yet recent reviews of virtual lab education found studies targeting it to be the exception rather than the rule (Brinson, 2015; Faulconer & Gruss, 2018). Recognizing this gap in research, in the summer of 2020, when our traditionally FTF introductory chemistry labs were moved online due to the pandemic, we developed a survey instrument aimed at quantifying our students’ perceptions of both their cognitive and affective learning online (Jones et al., 2021). Adapting an existing instrument from Galloway and Bretz (2015), we continued collecting student data as labs moved from online to hybrid and, most recently, back to fully FTF. (See the online appendix for a complete list of survey items.)

Study framework

In spring 2021, our General Chemistry 2 lab was delivered completely FTF for the first time in an academic year. Given a return to physical experimentation, we sought to understand how taking the prerequisite lab course (General Chemistry 1) online affected students’ expectations and experiences in the spring course. Using our same survey instrument, our study compared students who took the prerequisite course online in the fall with those who matriculated straight to General Chemistry 2. This study aimed to answer the following question: What is the effect on meaningful learning in later-sequence lab courses if the prerequisite lab is virtual?

Course description

This research was conducted at a large public university in the southeastern United States in a traditional FTF General Chemistry 2 laboratory course in spring 2021. The lecture and lab prerequisite course, General Chemistry 1, was offered fully online in fall 2020 in synchronous online delivery mode with a significant focus on small-group work (Jones et al., 2021). The 2-semester sequence of courses is geared toward science majors, engineering majors who will go on to take organic chemistry courses, and students interested in careers in health and medicine. To satisfy this General Chemistry 1 requirement, our institution also accepts a score of 4 or 5 on the College Board Advanced Placement (AP) Chemistry exam, a score of 730 or higher on the SAT chemistry subject exam, a score of 5 or higher on the International Baccalaureate high-level chemistry exam, or joint-enrollment or transfer equivalency credit. For the sake of simplicity, these alternatives for credit are referred to throughout this work as “external credit.” All of them give students the option to matriculate directly to General Chemistry 2.

The synchronous online delivery model of laboratory instruction involves the organization of students into groups of three or four in virtual breakout rooms. Experiments are centered on one or more simulations of chemical laboratory work from which data and observations are extracted. Students are provided with specific roles and work together under the supervision of a remote teaching assistant to complete the objectives of the experiment.

Methods

Assessment of student expectations and experiences was gathered through a previously validated survey designed to probe students’ perceptions of their own affective and cognitive learning in our laboratory courses (Jones et al., 2021). The 27-item survey was administered once during the first week of the semester to measure student expectations of the course (pre) and again during the final week of the semester to assess student perceptions of the experience (post). Each time, the survey was assigned for credit based on any level of participation; students who did not consent to the survey and indicated as such received the same credit as those who consented and fully responded. For each item, students indicated a percentage agreement with a given statement ranging from 0 (fully disagree) to 100 (fully agree). Approval for this study was obtained through our institution’s Institutional Review Board.

Data analysis

Descriptive statistics

Responses for negatively worded items were reverse coded to allow for meaningful comparison between items. Each item was categorized into either the affective or cognitive learning domain (three items were categorized as both) to allow for the calculation of composite average scores for each subgrouping. Only responses from students responding to both the pre- and postsurveys that passed an attention check were considered, and their responses were paired to allow for the calculation of subgrouping composite scores for each student based on (i) the presurvey, (ii) the postsurvey, and (iii) the relative change by item.

Students were grouped based on classification of the prerequisite General Chemistry 1 course, which they took in the fall 2020 semester or prior to fall 2020 or for which they received external credit. Given the low number of respondents who had taken General Chemistry 1 prior to fall 2020 (N = 9), this group was removed from the analysis to leave two student groups for comparison: those that took virtual General Chemistry 1 at our institution (VGC1, N = 258) and those with prior external credit (non-VGC1, N = 85). Both groups were majority first-year college students (VGC1 = 95%, non-VGC1 = 79%), making the distinguishing factor between the groups whether they had a previous chemistry course experience at our institution. Composite scores for these student groups were calculated (Table 1), and all sub data sets had acceptable Cronbach’s alpha values above 0.7, indicating reliable data sets. These data are further visualized in Figure 1.

Inferential statistics

Mixed repeated measure analyses of variance (mixed RM ANOVA) were performed for both item subgroupings to parse out differences between student groups and survey time points. For the affective item subgrouping, statistically significant differences were found within subjects (comparing paired pre- and postsurvey scores) as well as between student groups, but the effect sizes for both were small (Table 2). By contrast, RM ANOVA for cognitive item subgrouping found a significant difference within subjects with a large effect size (ƞ2 = 0.360) but no significant difference between student groups. Homogeneity of covariances and variances were confirmed in both RM ANOVA data sets, as seen in the nonsignificant values in Box’s and Levene’s tests.

Following these initial results, single-factor ANOVA were run to better narrow down the relationships between affective and cognitive learning when comparing time and student groups. Holding student group constant, cognitive pre- and postsurvey scores were significantly and practically different for both groups (VGC1 ƞ2 = 0.119, non-VGC1 ƞ2 = 0.142), but no difference was seen for affective scores. Conversely, when comparing the two student groups to each other at both survey time points, a difference was found between affective scores, but no difference was found between cognitive scores. The effect size for these observed affective differences was small (pre ƞ2 = 0.012, post ƞ2 = 0.019).

Results and discussion

The ANOVA results help us draw several preliminary conclusions (summarized by Figure 2). First, both student groups saw a meaningful decline in cognitive scores. The cognitive expectations and experiences were consistent between student groups, implying on average the decline in cognitive scores was independent of the type of prerequisite. Second, neither student group demonstrated a significant change in their perception of affective learning on average. However, comparing student groups to each other does elucidate a difference in both expectations and experiences of affective learning. This suggests the type of prerequisite course did play a role in students’ perceptions of their affective learning.

To better delve into the data, an item-by-item analysis was performed to find statistical differences on an item level. Paired t-tests were used to identify items with unequal expectations and experiences between student groups.

Consistencies between student groups

The ANOVA analyses deemed the composite affective scores for both student groups statistically different; it was no surprise, then, when only four of 16 affective items showed consistent pre- and postsurvey scores between the two student groups. These four items had a similar theme of a positive affinity for the subject of chemistry and the material in the lab sections (Table 3). We conclude from this grouping that the level of positive engagement students felt with their subject material was consistent whether or not their prerequisite experience was our General Chemistry 1 course.

Conversely, most cognitive items (8 of 14) had no meaningful differences between student groups (Table 4). Items fell thematically into two groups, either related to student interpretation of experiment data or skill acquisition and growth in the lab setting. We found this result surprising, as we anticipated the VGC1 group would have a cognitive advantage for interpreting data questions because they had just completed a semester of college chemistry lecture and labs. Consistency between student groups for these question types may be evidence of students compartmentalizing the prerequisite and current courses rather than envisioning them as continuous and connected. Given the difference in topic coverage in a General Chemistry 2 course as compared with its precursor, it is perhaps predictable that students may not constantly draw from their prior experience. This claim is bolstered by the same consistency in responses on items related to skill acquisition and growth.

Differences between student groups

Items with a theme related to performance and execution in the lab setting demonstrated that the non-VGC1 student group had an initial advantage over their VGC1 peers. These items were primarily affective, and this result was somewhat expected, as the VGC1 student group was coming straight from a semester of fully online chemistry labs, whereas the last chemistry experience for the non-VGC1 group may have been fully in person. We knew anecdotally that the VGC1 students were apprehensive about their lack of chemical lab experience, as seen in their comparatively much lower presurvey score for items 29 (“nervous to enter the physical lab space”) and 4 (“confused about what glassware would be needed to perform experiments”; Figure 3). For both of these items, postsurvey scores reasonably matched those of non-VGC1 students, indicating that by the end of the semester, these students were no longer disproportionately nervous about the lab space or confused by the glassware and tools.

Although the responses to item 29 indicate the VGC1 students felt much less nervous about working in the physical lab environment by the close of the semester, responses to item 7 (“nervous to make mistakes”) shows that these students were disproportionately concerned about errors in performance. Pairing this with responses to item 2 (“worried about finishing on time”), we see an underlying worry about both the speed and the accuracy with which students could work emerge for VGC1 compared with non-VGC1 students. These differences in perspective, despite both groups having the same lack of prior experience in a physical college chemistry lab, can perhaps be attributed to VGC1 students feeling underprepared from their online lab prerequisite. This may be evidence of students putting a greater emphasis on the psychomotor aspects of learning in the science laboratory setting than on cognitive or affective domains. Without the opportunity to practice physical techniques and skills in the online prerequisite course, VGC1 students may have been left with a residual feeling of nonequivalence in experience compared with a traditional in-person lab.

Pivoting to affective components of the course, one group of related items demonstrates the positive impact the VGC1 prerequisite had for its students. Two items asked students to reflect on the social and collaborative components of the course, for which VGC1 students scored significantly higher at both time points (Table 5, items 27 and 28). Presurvey scores made it especially clear that VGC1 students put a higher premium on working with classmates (item 27); we attribute this to the high volume of group work and collaboration in the design of the synchronous online prerequisite lab. Previous research has found that students in lab courses put a high weight on social components of courses (Miller et al., 2018). For VGC1 students, we rationalize that their collaborative experience in the prerequisite lab course intensified the positive perspective on peer collaboration and the social dimensions of learning, as items 27 and 28 had the highest average score of all items for VGC1 students.

In addition to the increased social experience of VGC1 students, stronger responses to items 13 and 21 demonstrate these students have a more resilient nature than their non-VGC1 counterparts (Table 5). This correlation supports the conclusion that any prior college lab experience—even one fully online—enables students to work through challenges. In fact, online labs may even aid more in this regard; with simulation-based labs, a student has greater opportunity to “fail safely,” as restarting an experiment is as simple as pushing a button. The ingrained opportunities offered by online labs to repeat experiments and procedures without the negative consequences experienced for the same in a traditional lab environment (longer lab time, potential demerits, safety and waste concerns) likely helps increase student willingness to be wrong in an effort to learn.

Although this impact on resiliency is encouraging when considering the potential future for online science labs, a cluster of affective items may also highlight a potential weakness of online prerequisites. VGC1 students had significantly lower pre- and postsurvey scores for items involving negative emotional experiences during their lab sessions (from left to right in Figure 4: felt overwhelmed, felt frustrated, felt anxious, felt intimidated). For each item, the expectations of both student groups were exceeded. In all four cases, the scores show nonequivalence in both the expectations and experiences between the two student groups. We hypothesize that the exaggerated perspectives of VGC1 students in presurvey scores stem from feeling behind after a semester of online labs—the same phenomenon that leads to increased worry about executing lab tasks. In this instance, we believe online labs had a negative impact. However, it is possible that this observed trend may be due to having any college chemistry lab experience, as students who have had any amount of college chemistry lab experience may be better informed about their more rigorous nature as compared with high school labs. A comparative study with an in-person VGC1 prerequisite would need to be performed to draw definitive conclusions.

Although it may be possible to explain how prerequisite course experience might influence student perceptions ahead of the course, prerequisite modality (remote or in person) does not adequately explain inequality seen in experiences (postsurvey scores). For all four items, the incremental gains for both student groups were remarkably similar. We are pleased that both student groups had their expectations exceeded across this cluster of items, but it would have been more satisfactory to also see statistically similar postsurvey scores. This trend across items may suggest that expectations for strong affective experiences predetermine the incremental change in perceptions that can occur. In other words, how negatively a student perceives a lab course at the start may influence their affective experience in the course.

Short-term implications for teaching

As of the writing of this article, many U.S. colleges and universities have reverted to “normal” lab instruction and away from online and hybrid modalities. After several semesters of majority or exclusively online learning experiences in higher education and high school, there are cohorts of students nationwide who are returning to physical lab spaces after completing online prerequisite lab courses. Although this study was conducted in a chemistry lab setting, we believe our findings will translate across lab-based science disciplines. We recommend that lab instructors inheriting students with prerequisite online lab experiences take the following steps:

1. Reaffirm the quality and parity of content covered by online prerequisite lab(s).
2. Directly address worries students may have about feeling behind in their psychomotor development.
3. Discuss with students the value of failure in learning, and create safe spaces for them to fail.
4. Affirm the importance of collaboration and social dimensions of learning for academic success.

Implications for laboratory education research

Understanding and quantifying student perceptions of their own learning need to be priorities equal to understanding how and why learning occurs in different environments. Self-perception in science courses has a proven correlation to science identity and efficacy (Trujillo & Tanner, 2014). Our study found evidence of an online prerequisite giving advantages to students in some ways (e.g., increased resiliency and buy-in for peers) and potential disadvantages in others (e.g., exaggerated apprehension related to physical lab work). As researchers, if we can better understand how and why different learning environments influence student perceptions of learning across learning domains, we can move forward with creating synergistic learning environments for students.

Additional considerations

We are intrigued to compare the current data with survey data gathered from students who take both General Chemistry 1 and General Chemistry 2 in a completely FTF mode in the upcoming academic year. Comparisons with FTF laboratory courses will further clarify the impact of virtual laboratories on subsequent learning and will help unveil the potential for virtual laboratory courses to enhance student experiences. Illuminating best practices for online or hybrid laboratory courses could help close equity gaps for some students. For example, as low-cost alternatives to expensive FTF laboratories, robust virtual laboratories can enable access to new modes of meaningful learning in science, technology, engineering, and mathematics (STEM) courses operating on tighter budgets.

As with all educational research completed over the past couple of years, the effects of the COVID-19 pandemic on this study cannot be ignored. In this study, for example, social isolation and the design and implementation of remote courses could play a significant role in the value students placed on interactions in the virtual lab spaces. It is reasonable to assume that students’ varied life experiences during this time also affected their perceptions in ways that cannot be measured. Unexplained variance due to variable impacts of the pandemic should be considered when interpreting the results of educational studies done during this time.

Conclusions

This study compared survey data in a General Chemistry 2 course for two student groups who differed in their mode of prerequisite lab course (online the semester prior or through external credit). Our analysis of student data found that, on average, the cognitive learning experience was equivalent regardless of prerequisite status, but affective learning differed significantly. Students who took the online prerequisite VGC1 course demonstrated greater resiliency and affinity for peer and instructor relationships but reported being slightly more intimidated, frustrated, and overwhelmed in the lab. Understanding how the mode of instruction of a prerequisite lab course affects learning in the next course is of the utmost importance to the science education community as we begin to enter the post–COVID-19 instructional period. Continued studies of meaningful learning in laboratory courses in all STEM disciplines would bring the community closer to this goal.

Elizabeth V. Jones (elizabeth_jones@hms.harvard.edu) is formerly a graduate student in the School of Chemistry and Biochemistry at the Georgia Institute of Technology in Atlanta, Georgia, and currently a postdoctoral research fellow in the Department of Biological Chemistry and Molecular Pharmacology at Harvard Medical School in Boston, Massachusetts. Michael Evans (michael.evans@chemistry.gatech.edu) and Carrie Shepler (carrie.shepler@cos.gatech.edu) are members of the teaching faculty in the School of Chemistry and Biochemistry at the Georgia Institute of Technology.